University of Leeds PhD student Ute Bradter has created an automated and predictive method of vegetation mapping with 92 percent accuracy that rivals comparable traditional mapping, but is much quicker and cheaper. The approach applied a statistical model with inputs on soil type, altitude, slope and aspect, with aerial images and Ordnance Survey maps, to predict the distribution of plants on the 1600 km2 Yorkshire Dales National Park Authority (YDNPA).
The resulting high-resolution vegetation map shows species distribution for 24 National Vegetation Classification groups across the area at a 5m resolution. The map will provide a valuable resource for land management, conservation planning, environmental monitoring and further research.
Co-author and Senior Wildlife Conservation Officer at YDNPA, Dr Tim Thom, says: “This method also has the potential to be used for a wide range of other environmental purposes, such as identifying rare habitat, or where drainage ditches are grown over and so pose a flood risk, or where erosion-risk is high in areas of bare peat. What’s most exciting is that if we can map the plants accurately, we can also make a better guess what animals live there too, so we could also remotely monitor biodiversity across the farmed habitat or predict the potential value of setting aside pockets of land for conservation as part of agri-environmental schemes.”
Results have been published in the British Ecological Society’s Journal of Applied Ecology, with details also outlined in this press release.
